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{\huge Algorithm acceleration with GPGPU} \\

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by \\
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{\Large Kevin Yang} \\
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A Thesis \\

Submitted to the Faculty \\

of the \\

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{\large WORCESTER POLYTECHNIC INSTITUTE}\\
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in partial fulfillment of the requirement for the \\
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Degree of Master of Science \\

in \\

Electrical Engineering \\
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August 2011 \\
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Approved
Dr. Xinming Huang, Thesis Advisor
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\begin{abstract}
We apply GPGPU programming toward the acceleration of financial algorithms.  
This thesis presents two financial algorithms and discusses the challenges and 
results of accelerating both through the use of GPGPUs, as well as a guide
to which algorithms the GPGPU is best suited for.
A speed up factor of
60 is acheived using the GPGPU. We will present the mathematics 
of the algorithms and the techniques for acceleration. Based on the results of
this research.  We believe that the 
speed up acheived by GPGPU technology will enable the deployment of more
computationally complex algorithms in a high frequency environment. 
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\begin{acknowledgements}
I would like to thank Xinming Huang for being my friend and advisor 
for the past year.  Xinming brought me into his lab and gave me his
full trust and support in this project.  Thanks to Aleks Chechkin for
giving me a glimpse of the traders world.  Aleks' energy and passion 
for what he does was an inspiration for me and helped me find motivation 
on off days.  Aleks was also instrumental in helping me understand 
the work and see the big picture and where this work would fit in.  
Thanks as well to Art Gerstenfeld and Emmanuel Agu of WPI.  The project
would not have happened without Art's persistence and connections and 
Emmanuel provided insight into the techniques and culture of financial
computing.  Thanks to Neil of BNP Paribas for signing off on the project
and giving us a chance.
\end{acknowledgements} 

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